/// <summary>
/// 绑定检测信息
/// </summary>
public void FaceTestBind(FaceCheckModel model)
{
//清空文本框
TestTextBoxAdd(textBox1, "", "", true);
if (model.Face_num > 0)
{
if (model.Face_list != null && model.Face_list.AsEnumerable() != null && model.Face_list.AsEnumerable().Any())
{
TestTextBoxAdd(textBox1, model.Face_num, "人脸数量为:");
TestTextBoxAdd(textBox1, "", "--------------------------------------");
int count = 0;
foreach (var item in model.Face_list)
{
count++;
TestTextBoxAdd(textBox1, "", $"当前检测第{count}张人脸{item.Face_probability * 100}%为一张真实人脸");
TestTextBoxAdd(textBox1, $"{item.Quality.Blur * 100}%", "人脸模糊程度 :");
TestTextBoxAdd(textBox1, item.Age, "年龄 :");
TestTextBoxAdd(textBox1, item.Beauty, "美丑打分 :");
TestTextBoxAdd(textBox1, item.Gender.Type.GetEnumDescription() + $" 概率为{item.Expression.Probability * 100}%", "性别 :");
TestTextBoxAdd(textBox1, item.Expression.Type.GetEnumDescription() + $" 概率为{item.Expression.Probability * 100}%", "表情 :");
TestTextBoxAdd(textBox1, item.Emotion.Type.GetEnumDescription() + $" 概率为{item.Emotion.Probability * 100}%", "情绪 :");
TestTextBoxAdd(textBox1, item.Glasses.Type.GetEnumDescription() + $" 概率为{item.Glasses.Probability * 100}%", "是否带眼镜 :");
TestTextBoxAdd(textBox1, $"左眼未闭合概率为{item.Eye_status.Left_eye*100}%,\r\n\r\n右眼未闭合概率为{item.Eye_status.Right_eye * 100}%", "右眼闭合状态 :");
TestTextBoxAdd(textBox1, item.Race.Type.GetEnumDescription() + $" 概率为{item.Race.Probability * 100}%", "人种 :");
TestTextBoxAdd(textBox1, item.Face_shape.Type.GetEnumDescription() + $" 概率为{item.Face_shape.Probability * 100}%", "脸型 :");
TestTextBoxAdd(textBox1, item.Face_Type.Type.GetEnumDescription() + $" 概率为{item.Face_Type.Probability * 100}%", "真实人脸/卡通人脸 :");
TestTextBoxAdd(textBox1, "", "--------------------------------------");
}
}
}
else
{
TestTextBoxAdd(textBox1, "", "未获取到人脸信息,或者网络异常!");
}
}
/// <summary>
/// 人脸检测
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void skinButton1_Click(object sender, EventArgs e)
{
if (picbPreview.Image is null)
{
MessageBox.Show("请先拍照或者选取一张图片,再进行检测操作");
return;
}
// var APP_ID = "17894506";
Thread threadadd = new Thread(() =>
{
try
{
var client = new Baidu.Aip.Face.Face(API_KEY, SECRET_KEY)
{
Timeout = 60000 // 修改超时时间
};
var image = ImgToBase64String((Bitmap)this.picbPreview.Image);
var imageType = "BASE64";
// 调用人脸检测，可能会抛出网络等异常，请使用try/catch捕获
var result = client.Detect(image, imageType);
// 如果有可选参数
var options = new Dictionary <string, object>
{
{ "face_field", "age,beauty,expression,face_shape,gender,glasses," +
",race,quality,eye_status,emotion,face_type,eye_status" },
{ "max_face_num", Max_face_num },
{ "face_type", "LIVE" },
{ "liveness_control", "LOW" }
};
// 带参数调用人脸检测
result = client.Detect(image, imageType, options);
if (result != null && result.ToString() != null && result.ToString().Length > 0)
{
var json = JsonConvert.SerializeObject(result);
FaceCheckModel model = DeserializeJsonToObject <GetApiJson <FaceCheckModel> >(json)?.Result ?? new FaceCheckModel();
FaceTestBind(model);
}
;
var picclient = new Baidu.Aip.ImageClassify.ImageClassify("NpBGfUR6qBGtFo5bIFbiPCO9", "S0L7LXAewfW7BBKmbXd0EQ8iRzEYRGqc")
{
Timeout = 60000 // 修改超时时间
};
Image img = this.picbPreview.Image;
MemoryStream ms = new MemoryStream();
byte[] imagedata = null;
img.Save(ms, System.Drawing.Imaging.ImageFormat.Jpeg);
imagedata = ms.GetBuffer();
var picoptions = new Dictionary <string, object> {
{ "baike_num", Result_num }
};
var results = picclient.AdvancedGeneral(imagedata, picoptions);
if (results != null && results.ToString() != null && results.ToString().Length > 0)
{
var json = JsonConvert.SerializeObject(results);
ImageRecognitionModel model = DeserializeJsonToObject <ImageRecognitionModel>(json) ?? new ImageRecognitionModel();
ImageRecognitionBind(model);
}
}
catch (Exception ex)
{
MessageBox.Show("网络错误！错误信息:" + ex.Message);
}
});
threadadd.Start();
}